Model lifecycle & governance
Domino AI Governance
Governance layer of the Domino enterprise data science platform: an MLflow-based model registry with project- and deployment-scoped views, custom model cards, version management, RBAC over registered models and stage transitions, plus documented review steps for validation, ethical review, audit trails and stakeholder sign-off.
commercial · generally available · Research snapshot 2026-09-06
Visit the official product source ↗Where it fits
Model lifecycle & governance · AI risk & compliance management
Useful conversation with: Head of data science, Model risk manager, ML platform owner.
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Show me role-based control over stage transitions in the Domino model registry and the self-documenting evidence produced for a model review.
Capabilities and evidence
Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.
Documented by provider
Domino documentation states its MLflow-based model registry supports project-scoped and deployment-scoped discovery, records model metadata and lineage, creates custom model cards, manages model versions, deploys to Domino-hosted or external endpoints, and uses RBAC and project roles to limit who can view, edit and collaborate on registered models.
Limit: Docs state RBAC over registry actions but do not document a formal multi-step approval workflow.
Source s1
Documented by provider
Domino documentation on reviewing and approving models states role-based permissions regulate who can transition models into different stages so only authorized personnel can approve moves to production, and describes a governance framework including model validation, ethical review, audit trails and stakeholder review.
Limit: The page describes a governance framework and permission model, not automated enforcement against named regulations.
Source s2
Vendor claim
Domino's product page claims AI policies embedded in workflows with policy enforcement, a central model registry, centralized policy management, self-documenting evidence, model cards for AI compliance, full model lineage and automated documentation.
Limit: Marketing page; framework mappings and enforcement mechanics are not evidenced there.
Source s3
Limitations to discuss
- Registry capability is built on MLflow, so some behaviour is inherited from that project rather than Domino-specific.
- No evidence of EU AI Act / ISO 42001 control mappings on the pages fetched.
Sources
- Manage models with model registry · Domino Data Lab · official docs
Access date reported by researcher: 2026-09-06 - Review and approve models · Domino Data Lab · official docs
Access date reported by researcher: 2026-09-06 - AI governance platform | Domino Data Lab · Domino Data Lab · official product
Access date reported by researcher: 2026-09-06
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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